Information retrieval, in the form of full text searching, is a rapidly growing aspect of the function of most computer systems. The ability to efficiently conduct full text searches is a crucial component for computer systems in both local area network settings, such as an intranet, and wide area network settings, such as the Internet.
Generally described, full text searching can be facilitated through one or more indexes that can be queried. In a typical embodiment, a computer system can include a data parsing/index generating component that extracts information from a data set. The data parsing/index generation component then generates one or more searchable indices correspond to an analysis of the data set. For example, in one approach, the component generates an inverted keyword index that tracks keywords as they are found in the set of data. Additionally, the computer system can include a query engine that receives the index from the data parsing/index generating component and subsequently processes data queries.
Although components and data structures such as the data parsing/index generating component, the query engine and the keyword indices can facilitate full text searching, traditional implementations of these components and data structures can become deficient for a variety of reasons. In one aspect, scaling issues can occur as querying of traditional keyword indices becomes more inefficient with the size of the index. In another similar aspect, the passing of keyword index data between the data parsing/index generating component and the query engine can result in an increased burden on system memory resources. In a further aspect, traditional interoperability between the data parsing/index generating component and the query engine can often result in a delay of the availability of updated indexes for searching by the query engine.
Thus, there is a need for a system and method for facilitating full text searching utilizing inverted keyword indices that can improve scalability and process interoperability.